Adaptive Learning: Reinforce Knowledge and Fight the Forgetting Curve

06February 2018

The success of any business directly depends on how well its workforce is trained. The American Society for Training & Development indicates that small and mid-sized companies allocate $1,605, on average, to employee training programs. Organizations worldwide spend more than $350 billion on training. However, to see the real state of things, you can take half of that training budget and throw it away. Why? This is a result of the forgetting curve.

Unfortunately, people tend to forget things. In fact, figures show that we forget up to 75% of information within the first 24 hours and about 90% within a week. In a month or so, we would remember only 2%-3% of the material if we make no attempt to retain it.

Understand how memory works to reinforce knowledge

In 1885, German psychologist Hermann Ebbinghaus introduced the notion of the forgetting curve, stating that the information is lost over time when there is no attempt to retain it. This phenomenon is quite natural. Every day, our brain receives a lot of information about the environment we are in that may or may not directly influence us. Where did you park your car yesterday? What color hair did that tall stranger have? What was the name of the sales assistant who helped you choose a good shampoo? To avoid information overload, our brain discards all the irrelevant details that won’t come up again or have no practical value.

Unfortunately, even necessary information suffers the same fate. Remember your school years? Your teacher announces that you will have a test on algebra the next week and gives you a study guide. You look through the questions and come to the conclusion that you don’t remember half the material. This can be partially explained by the decay theory and the interference theory. The former suggests that we eventually forget things we don’t retrieve from time to time. The latter states that interference happens when a fresh piece of information we’ve recently learned makes it harder for us to remember previously learned material. This means that what we do with the information after learning is more important than what we do in the process. However, it’s not only about forgetting. Sometimes our brain fails to transfer important things to long-term memory.

If you want to make information stick, it’s best to learn it, go away from it for a while, come back to it later, leave it behind again, and once again return to it—to engage with it deeply across time. Our memories naturally degrade, but each time you return to a memory, you reactivate its neural network and help to lock it in.

The relevance of information. Practicality creates interest. If you learn something that can be translated into action to solve a challenge, you will remember the material better.

The way information is acquired. Think of what is the best way for you to remember the material? Do you prefer to read a book? Watch a video? Listen to a podcast? Look through diagrams, infographics, or pictures?

Why adaptive learning is a go-to solution for effective training

Adaptive learning is a form of continuous, non-linear, data-driven, adjustable learning that utilizes an employee’s performance and preferred learning style to ensure effective training.

What makes adaptive learning so effective is that it can be different for different people and offers more than what personalized training does. Personalization is a good starting point. It takes into account the department where an employee works, their job position, key responsibilities, educational background, as well as current knowledge and skill level. This information helps to define an initial learning path. Then the ability to adapt comes into play; since an employee keeps developing, adaptive learning technology develops as well to meet the individual’s growing needs. It gathers data and processes it, following their progress.

Dr. Chris Littlewood, co-founder and Head of Science at Filtered, believes that the future of corporate training is governed by adaptive learning and further explains its application:

The process can be broken down into 3 stages: personalisation—not only what the user will learn about, but also how, and why; the data challenge—how information gathered as the user progresses through modules can be used to further personalise the training, through the examination of which learning techniques have proved to work the best; usefulness—data and results can be stored and used to establish how effective a course was, and provide a better platform for future courses which can be quickly tailored to existing users.

Following the way the adaptive technology works, we can single out two key advantages:

Flexibility. Adaptive technology allows to trace individuals’ preferences in how they better acquire new skills and knowledge, define which learning style suits them best, and offer the most appropriate type of content (videos, podcasts, articles, charts, etc.). Moreover, if the system detects that a user has some difficulties with a subject, it can provide additional learning material within a subject to ease the process and/or offer external links for better understanding. By combining elements of microlearning and just-in-time training, the system also offers short bits of material when users need it no matter where they are. Instant accessibility and various types of content make learning smoother and more meaningful.

Relevance. All learners differ by level of proficiency. Instead of making everybody learn the same content, adaptive learning technology filters the information, discarding irrelevant material. Say your employees are required to complete a module. Firstly, the system will make them go through an initial diagnostic test to define what they already know and what they need to know. For example, if a module consists of submodules A to G, then some of your employees may have to learn modules A, B, and F; some will learn B, G, and E; and some would need to learn all of them. Thus, adaptive technology will not only save time but also increase engagement, as your employees will learn only relevant information to bridge the knowledge gap.

Adaptive learning can be broadly used in all industries and spheres. Consider how it can help to develop leadership skills. Marcus Buckingham, author, speaker, and business consultant, in a 2012 Harvard Business Review article said that “even in firms where leadership development is a priority, the content served up is generic—it shows little understanding of you.” In collaboration with Hilton Worldwide, they created an app that was designed to train managers based on their leadership styles. Buckingham explained that every time users interacted with the app, the system changed dynamically with managers’ progress, providing the most suitable content for every user. He further described how the adaptive technology worked within the app:

Intrinsic to the notion of a personalization algorithm is that it must get to know you better over time. With every interaction, the app adds detail to your leadership profile. As you rate the effectiveness of the techniques you receive, the system tracks your reactions and becomes smarter about which techniques to feed you. As the sample size of leaders, techniques, and reactions grows, this two-way communication channel should become as good as the very best consumer recommendation engine at offering content that is relevant to you.

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